pith:TAIAO7EI
RouterWise: Joint Resource Allocation and Routing for Latency-Aware Multi-Model LLM Serving
Jointly tuning GPU shares and routing fractions across models raises output quality by up to 87 percent while meeting a fixed latency target.
arxiv:2604.10907 v2 · 2026-04-13 · cs.NI · cs.DC
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Claims
even on the same GPU cluster, achievable output-quality score can vary by up to 87% across retained setups, highlighting that resource allocation is a key determinant of routing performance.
The latency models obtained from system profiling accurately predict end-to-end latency when the routing policy induces a particular load on each model under a chosen resource allocation.
Joint resource allocation and routing for multi-model LLM serving can produce up to 87% variation in achievable output quality across setups on the same GPU cluster.
Receipt and verification
| First computed | 2026-06-23T02:13:23.752366Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
9810077c88faba0c5fadcf896e51475139b565c320149bddc58b74d993b89d82
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/TAIAO7EI7K5AYX5NZ6EW4UKHKE \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 9810077c88faba0c5fadcf896e51475139b565c320149bddc58b74d993b89d82
Canonical record JSON
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